COS 35-1 - Do climatic constraints on American-pika distribution vary spatially, and if so, how? Tests of common SDM assumptions, and novel approaches to improve modeling

Tuesday, August 8, 2017: 8:00 AM
D131, Oregon Convention Center
Erik A. Beever1, Adam B. Smith2, Aaron N. Johnston3 and Mimi Kessler2, (1)Ecology Dept., Montana State University, Bozeman, MT, (2)Center for Conservation and Sustainable Development, Missouri Botanical Garden, Saint Louis, MO, (3)Northern Rocky Mountain Science Center, U.S. Geological Survey, Bozeman, MT

Species distributions reflect innumerable factors that constrain any single species’ distribution from its fundamental to realized niche, including aspects of the predatory, competitive, and physical environments. Niches are known to be constrained by different factors over small spatial extents (e.g., upper- vs. lower-elevation edges of occupancy, within mountains); furthermore, species-climate relationships may reflect clinal variability in climate, local adaptation, and ecological context. Despite these facts, thousands of species-distribution models (SDMs) forecast with spatially-unvarying predictors. Because American pikas are known to respond to variability in climatic conditions at multiple spatial and temporal scales, we are using species distribution modeling (with Maxent, boosted-regression trees, and GAMs) to challenge the assertion that climate constrains distribution via the same climate-aspect and functional form across all parts of a species’ range. Using data from >85 contributors, we are designing novel ways to rigorously: a) define the ‘background’ available to individual pika detections; b) compare predictive ability of several schemes of subdividing the species range into subunits; c) quantify the consequences of correcting for spatial, temporal, and spatio-temporal bias; and d) assess the degree of overlap in importance of climatic predictors, across subunits.


We find strong differences in relative importance of species-distribution determinants in different ecoregions within the geographic range. Choosing several hierarchical-classification schemes, guided by hypothesized mechanisms of climate influence on populations and deep understanding of the species’ life-history characteristics, we find that certain characteristics (e.g., snow-pack variability) appear in SDMs trained and tested on each of the five phylogenetic clades, albeit in different functional forms. Pika detections only occasionally overlap in (multivariate) ordination space, but this partly reflects some discrimination (i.e., non-overlap) of the background available to each lineage. When investigating transferability of SDMs among clades, chronic-heat stress and climatic water availability showed strongest relationships among groups. Deeper initial investigations into phylogenetically defined niches suggest that evolutionary pathways proposed by Galbreath (2009) are not reflected in our analyses, but that the fenisex lineage has a markedly distinct niche from the rest of the species. Fine-scale analyses will seek to identify the locale-specific factors constraining pika distribution and thus identify possible mechanisms to address in any climate-adaptation conservation actions.